2 papers
cs.LG2025
Future Aware Safe Active Learning of Time Varying Systems using Gaussian Processes
Markus Lange-Hegermann, Christoph Zimmer
Experimental exploration of high-cost systems with safety constraints, common in engineering applications, is a challenging endeavor. Data-driven models offer a promising solution,…
cs.LG2024
Efficiently Computable Safety Bounds for Gaussian Processes in Active Learning
Jörn Tebbe, Christoph Zimmer, Ansgar Steland +2
Active learning of physical systems must commonly respect practical safety constraints, which restricts the exploration of the design space. Gaussian Processes (GPs) and their cali…